Chatster · B2C · AI chat app
Spin off an AI Bible app for chat users who asked religious questions
Sold at $29.99 lifetime with little effort; ads near break-even
What they did
What happened
In their words
How He Built an $800K ARR App Using Simple Strategies
… you can build apps for five different types of concepts right and then you test the concept right and then you find which concept makes you the most money and that's when you invest and maybe I'll find maybe they don't make any money and then you have to say okay forget it but at least you didn't spend a lot of time and money on something that doesn't work right um so i love it uh you know this is our we we got into so our chatster app i'll give
you a little background this real quick our chatster app is an you know it's an ai app and we dug in some of the data and we found that um people who do religious queries really are stick around right they're they're just they love they love ai they love a whole lot of stuff so you know and so we said okay let's do it let's let's see how you know let's do a specific bible app for it So we did a Bible app and, but once again, we had to go through the process, right? And proof of pay is all about ladders, right? You start with a low price and you work your way up to you find a price that works, right?
And if you don't find a price that works like this 29, you know, you kind of say, oh my God, if I can't, if I can't get past 499, then there's a problem, right? Then you kind of go on to the next concept, right? And our concept right now is understanding the Bible, right? Using AI to help people really dig into the meaning of the Bible. if they're stuck on a verse or they want to relate it to their own personal life. They want context. They want …
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More from this episode
- Turn a $5.99 paid app into a free download with a subscriptionRevenue jumped from ~$200/day to ~$2,000/day overnight
- Sell lifetime access instead of subscriptions unless the app has real running costsWorks well across their apps; subscriptions drew complaints on one
- Offer $59.99 lifetime or $39.99/year with a 3-day trial on a closable paywall~6% of installs buy; best revenue per 1,000 users of the variants tested
- Keep installs about half organic, half paid; fund only channels returning 2-3xOn track for ~110K MRR
- Use Apple Search Ads only if the cost per install fits your numbersBest paid channel for this app; too pricey for many of their others
- Run Google and Bing search ads and feed sales back to them every nightTwo of the three main paid channels; Bing small but profitable
- Test a one-screen landing page against sending search clicks straight to the App StoreDepends on the app; no general rule
- Test lifetime prices from $4.99 up to $49.99 at fixed ad spend to find the ceiling$29.99 beat $49.99 on day-one revenue; a later $39.99 now beats $29.99
- Build quick AI-coded versions of several app ideas; keep the one that sells
- Launch with a hard paywall, one offer and no free trialOne offer gave the clearest pricing lessons
- Test with exact-keyword Apple Search Ads, then scale on MetaMeta converted even better than Apple Search Ads
- Set Meta ads to find buyers, not installs, and test videos at ~$500/dayInstall-to-purchase rose from ~6% to ~18-20%
- Title the App Store page with plain search terms and put the brand last
- Test app icons first, including wildly different versionsGuest says icons move conversion most; no numbers
- Test dropping the onboarding screens entirelyNo onboarding won in several apps; even one welcome screen hurt
- Use Adapty to change prices and paywalls without an app update
- Show one offer on the paywall with a 'view all plans' link
- Lay out paywall plans side by side instead of stacked~2 points higher conversion (guest unsure of the exact number)
- Skip paid attribution tools; use Meta's own numbers, in-house tracking and Mixpanel
- Put a hard paywall with one lifetime price on an app ranking in search
- Run Meta ads at ~$150/day for a fitness app for people 65+Nobody bought after $3-5K; buyers came from App Store search
Tags: spin-off, usage-data, vertical-ai